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   "source": [
    "# 《Python数据分析基础 — 数据可视化（第2版）》\n",
    "## 习题8\n",
    "## 二、计算题\n",
    "**（请在问题下面的空白框写出代码并执行以输出结果）**"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "1. AirPassengers数据集[数据来自Python数据包pydataset]包含了1949～1960年间的月度国际航班乘客总人数的数据。\n",
    "   该数据是时间序列格式，单位为千人。\n",
    "   "
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "（1）请画出该数据的折线图。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "（2）分别用趋势预测方法和平滑预测方法进行预测。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "（1）做speed与dist的散点图，并以此判断speed与dist之间是否大致呈线性关系。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "2. BJsales数据集[ 数据来自Python数据包pydataset]包含了销售数据（BJsales）和其先行指标（BJsales.lead）的数据，数据是时间序列格式。"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "（1）请画出该数据的折线图。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "（2）分别用趋势预测方法和平滑预测方法进行预测。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "3. EuStockMarkets数据集[ 数据来自Python数据包pydataset]包含了1991～1998年间欧洲主要股票交易市场的日收盘价。\n",
    "   该数据是时间序列格式，由1860行和4个变量构成。4个变量分别代表欧洲的4个\n",
    "   主要股票市场：Germany DAX (Ibis)，Switzerland SMI，France CAC，UK FTSE。"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "（1）请画出该数据的折线图。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "（2）分别用趋势预测方法和平滑预测方法进行预测。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "4. JohnsonJohnson数据集[ 数据来自Python数据包pydataset]包含强生公司1960～1980年间的季度收入。该数据是时间序列格式。   "
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "（1）请画出该数据的折线图。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "（2）分别用趋势预测方法和平滑预测方法进行预测。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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